Identifying sources of interference in civil aviation radio communication

Civil aviation is an important part of public transportation. However, the wireless communication systems used in the approach and tower control phases of traffic control are susceptible to external interference, posing a threat to flight safety. Traditional communication interference solutions are time-consuming and require specialized technicians to troubleshoot. To solve this problem, we propose a real-time method for monitoring abnormal signals and detecting interference sources during aviation radio communications. The method consists of three steps: real-time blind source signal separation using cubic polynomial fitting, abnormal signal monitoring based on discriminative signal residence time, and using Pearson correlation coefficients to identify abnormal interference sources. This comprehensive approach effectively ensures the frequency safety of aviation radio communications. Experiments conducted at different locations in real airport environments demonstrate that this method can efficiently identify the signal bands and their interference sources.